Aula Pacinotti e online
link
https://teams.microsoft.com/dl/launcher/launcher.html?url=%2F_%23%2Fmeet%2F3945759878175%3Fp%3DNcfksLI2nDaFg2dcvn%26anon%3Dtrue&type=meet&deeplinkId=3d5a52cb-0bba-43eb-b585-1a5081499c51&directDl=true&msLaunch=true&enableMobilePage=true&suppressPrompt=true
Xiaomeng Li
Department of Electronic and Computer Engineering,
The Hong Kong University of Science and Technology,
Hong Kong SAR
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Abstract:
This talk will explore the latest advancements in artificial intelligence (AI) methods for medical image analysis and their contributions to accurate and robust medical image understanding. First, I will present our recent progress in large vision-language foundation models and their clinical significance across various applications. Next, I will showcase our work, including how these methods can benefit clinicians and patients. Finally, I will discuss opportunities for future research in this rapidly evolving field.
Bio
Prof Xiaomeng Li is an Assistant Professor in the Department of Electronic and Computer Engineering and the Department of Computer Science and Engineering at The Hong Kong University of Science and Technology. She also serves as the Associate Director of the HKUST Center for Medical Imaging and Analysis. Prior to joining HKUST, she was a postdoc at Stanford University and earned her Ph.D. from The Chinese University of Hong Kong. Her research focuses on the interdisciplinary field of artificial intelligence algorithm innovation and clinical applications in medicine. She is dedicated to leveraging artificial intelligence to enhance diagnostic efficiency, optimize clinical treatment environments, and promote the development of patient-centered precision medicine. With extensive research experience in this domain, Dr. Li has authored or co- authored over 100 high-quality journal and conference papers as the first or corresponding author.
Her work has been published in prestigious journals such as Nature Communications, IEEE Transactions on Medical Imaging, as well as in top-tier conferences including CVPR, NeurIPS, ICCV, MICCAI, and ICLR. Several of her papers were selected for oral presentations at ICCV and MICCAI (with acceptance rates below 3%).
Prof Li and her team have achieved outstanding results in multiple international medical imaging competitions, including winning championships in the International Liver Tumor Segmentation Challenge, the Intervertebral Disc Localization and Segmentation Challenge, and the MICCAI
Endoscopic Surgical Video Analysis EndoVis-SynISS Challenge. She has also received prestigious awards such as the MICCAI 2020 NIH Award and the MICCAI DeCaF Best Paper Award. She holds 10 international and Chinese patents, demonstrating the translational potential and innovative value of her research contributions.
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